Workpiece positioning and identification method based on image segmentation

Abstract

The invention relates to a workpiece positioning and identification method based on image segmentation. The method comprises three stages of pre-processing, workpiece region positioning and segmentation and characteristic extraction and identification, for pre-processing, de-noising for an image for a workpiece on a conveying belt is carried out, gray stretch image enhancement for the image after de-noising is carried out, operation like thresholding is then carried out, the purpose is to highlight a workpiece region of the image, and preparation for positioning the workpiece region is carried out; for workpiece region positioning and segmentation, on the basis of a minimum enclosing rectangle segmentation algorithm, the workpiece region is framed by a minimum enclosing rectangle, and a workpiece region image in the minimum enclosing rectangle is then acquired through cutting and is taken as a characteristic extraction image; for characteristic extraction and identification, an invariant moment of the image and geometric characteristics of the image are extracted and taken as a characteristic set for classifier training, and multiple characteristics of various workpieces are taken as a training sample set to train classifiers. The method is advantaged in that algorithm design is simple and rapid, not only can accurate positioning be guaranteed, but also real-time demands on a pipeline can be further satisfied, and thereby positioning and identification of the workpiece on the conveying belt are realized.

Description

technical field [0001] The invention relates to a method for positioning and identifying workpieces based on image segmentation, which belongs to the field of machine vision. Background technique [0002] With the rapid development of computer technology and digital image processing, machine vision has been widely used in the fields of national economy, scientific research and national defense construction. As the main means for industrial robots to obtain external environmental information, machine vision can improve the flexibility and automation of industrial production. Its biggest advantage is that it has no contact with the observed object and will not cause damage to the observed object. The environment is used in place of the tireless, consistent observation of the detected object by a human. In the traditional assembly line, the operation of the assembly robot can only complete the material handling, assembly, and workpiece transfer and loading and unloading on the...

AI Technical Summary

Problems solved by technology

In the traditional assembly line, the operation of the assembly robot can only complete the material handling, assembly, and workpiece transfer and loading and unloading between the stations through point-by-point teaching. It can only do some fixed actions, but the industrial site environment Complicated, the workpiece pose is randomly placed, and the position of the actual target workpiece is easily deviated from the ideal workpiece pose, which makes the industrial robot unable to successfully complete the operation task

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